OpenCV实现Matlab的fspecial('gaussian',m,sigma) 生成高斯核 C

Matlab: function K = kernal(sigma) m = ceil(2*sigma+1); K = fspecial('gaussian',m,sigma);

VS2008 C++ OpenCV:

Mat gaussian_kernal(int sigma)//sigma既是高斯核半径，又是真正的sigma { int dim = ceil(2.0 * sigma + 1); //高斯核大小为dim*dim Mat K(dim, dim, CV_32FC1); //生成二维高斯核 float s2 = 2.0 * sigma * sigma; for(int i = (-sigma); i <= sigma; i++) { int m = i + sigma; for (int j = (-sigma); j <= sigma; j++) { int n = j + sigma; float v = exp(-(1.0*i*i + 1.0*j*j) / s2); K.ptr(m)[n] = v; } } Scalar all = sum(K); Mat gaussK; K.convertTo(gaussK, CV_32FC1, (1/all[0])); return gaussK; }

//再来一个既含有高斯核直径kernelSize，又有单独的sigma的版本： //double sigma0 = (halfSize - 1)/ 2.0; Mat gaussian_kernal(int kernelSize, double sigma0) { int halfSize = (kernelSize-1)/ 2; Mat K(kernelSize, kernelSize, CV_32FC1); //生成二维高斯核 double s2 = 2.0 * sigma0 * sigma0; for(int i = (-halfSize); i <= halfSize; i++) { int m = i + halfSize; for (int j = (-halfSize); j <= halfSize; j++) { int n = j + halfSize; float v = exp(-(1.0*i*i + 1.0*j*j) / s2); K.ptr(m)[n] = v; } } Scalar all = sum(K); Mat gaussK; K.convertTo(gaussK, CV_32FC1, (1/all[0])); return gaussK; }

【OpenCV实现Matlab的fspecial('gaussian',m,sigma) 生成高斯核】